Publication

Abstract : Gait abnormality is the most significant symptom in the neurologically affected patients. To improve their quality of life, it is important to complement and further enhance the existing qualitative gait analysis protocol with a technically sound quantitative paradigm. In this paper, we present a pilot study and the development of a wearable intention detection and gait recognition (IDGR) system. This system comprises a well-established integrated network of microcontrollers and sensors which acts as a diagnostic tool for gait correction. IDGR system provides real-time feedback of the temporal gait parameter on a user interface. Furthermore, this system classifies the subject's intention - standing still, walking or ascending the stairs using simple logic inherent to an individual's walking style. It offers reliable tools for functional assessment of the patient's progress by measuring physical parameters. We conducted an experiment on a healthy participant as a validation of our approach and proof-of-concept.